Sensor deployment for pipeline leakage detection via optimal boundary control strategies

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2015, 11(1): 199-216. doi: 10.3934/jimo.2015.11.199

Sensor deployment for pipeline leakage detection via optimal boundary control strategies

Chao Xu ^1, , Yimeng Dong ^1, , Zhigang Ren ^1, , Huachen Jiang ^2, and Xin Yu ^3,

1.	State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems & Control, Zhejiang University, Hangzhou, Zhejiang 310027, China, China, China
2.	Institute of Operations Research & Cybernetics, Zhejiang University, Hangzhou, Zhejiang 310027, China
3.	Ningbo Institute of Technology, Zhejiang University, Hangzhou, Zhejiang 310027, China

Received December 2012 Revised January 2014 Published May 2014

Abstract
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We consider a multi-agent control problem using PDE techniques for a novel sensing problem arising in the leakage detection and localization of offshore pipelines. A continuous protocol is proposed using parabolic PDEs and then a boundary control law is designed using the maximum principle. Both analytical and numerical solutions of the optimality conditions are studied.

Keywords: Offshore pipeline network, leakage detection, optimal control., continuation approach, multi-agent system, partial differential equations, Lagrangian sensor.

Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C3.

Citation: Chao Xu, Yimeng Dong, Zhigang Ren, Huachen Jiang, Xin Yu. Sensor deployment for pipeline leakage detection via optimal boundary control strategies. Journal of Industrial & Management Optimization, 2015, 11 (1) : 199-216. doi: 10.3934/jimo.2015.11.199

References:

[1]	N. Ahmed and K. Teo, Optimal Control of Distributed Parameter Systems,, North Holland, (1981).
[2]	S. Anita, V. Arnautu and V. Capasso, An Introduction to Optimal Control Problems in Life Sciences and Economics,, Modeling and Simulation in Science, (2011). doi: 10.1007/978-0-8176-8098-5.
[3]	V. Arnautu and P. Neittaanmaki, Optimal Control from Theory to Computer Programs,, Kluwer Academic, (2003). doi: 10.1007/978-94-017-2488-3.
[4]	P. Barooah, P. Mehta and J. Hespanha, Mistuning-based control design to improve closed-loop stability margin of vehicular platoons,, IEEE Transactions on Automatic Control, 54 (2009), 2100. doi: 10.1109/TAC.2009.2026934.
[5]	S. Blazic, D. Matko and G. Geiger, Simple model of a multi-batch driven pipeline,, Mathematics and Computers in Simulation, 64 (2004), 617. doi: 10.1016/j.matcom.2003.11.013.
[6]	F. Bullo, J. Cortes and S. Martinez, Distributed Control of Robotic Networks (In Applied Mathematics Series),, Princeton University Press, (2009).
[7]	M. Chen and D. Georges, Nonlinear optimal control of an open-channel hydraulic system based on an infinite-dimensional model,, in Proceeding of the Conference on Decision and Control, (1999).
[8]	H. Cho and G. Hwang, Optimal design for dynamic spectrum access in cognitive radio networks under rayleigh fading,, Journal of Industrial and Management Optimization, 8 (2012), 821. doi: 10.3934/jimo.2012.8.821.
[9]	E. Chow, L. Hendrix, M. Herberg, S. Itoh, B. Kong, M. Lall and P. Srevens, Pipeline Politics in Asia: The Intersection of Demand, Energy Markets, and Supply Routes,, National Bureau of Asian Research, (2010).
[10]	Y. Ding and S. Wang, Optimal control of open-channel flow using adjoint sensitivity analysis,, Journal of Hydraulic Engineering-ASCE, 132 (2006), 1215. doi: 10.1061/(ASCE)0733-9429(2006)132:11(1215).
[11]	Z. Feng, K. Teo and V. Rehbock, Branch and bound method for sensor scheduling in discrete time,, Journal of Industrial and Management Optimization, 1 (2005), 499. doi: 10.3934/jimo.2005.1.499.
[12]	Z. Feng, K. Teo and V. Rehbock, Hybrid method for a general optimal sensor scheduling problem in discrete time,, Automatica, 44 (2008), 1295. doi: 10.1016/j.automatica.2007.09.024.
[13]	G. Ferrari-Trecate, A. Buffa and M. Gati, Analysis of coordination in multi-agent systems through partial difference equations,, IEEE Transactions on Automatic Control, 51 (2006), 1058. doi: 10.1109/TAC.2006.876805.
[14]	P. Frihauf and M. Krstic, Leader-enabled deployment onto planar curves: A pde-based approach,, IEEE Transactions on Automatic Control, 56 (2011), 1791. doi: 10.1109/TAC.2010.2092210.
[15]	R. Glowinski, J. Lions and J. He, Exact and Approximate Controllability for Distributed Parameter Systems: A Numerical Approach,, (Encyclopedia of Mathematics and its Applications) Cambridge University Press, (2008). doi: 10.1017/CBO9780511721595.
[16]	H. Hao and P. Barooah, On achieving size-independent stability margin of vehicular lattice formations with distributed control,, IEEE Transactions on Automatic Control, 57 (2012), 2688. doi: 10.1109/TAC.2012.2191179.
[17]	H. Hao, P. Barooah and P. Mehta, Stability margin scaling laws for distributed formation control as a function of network structure,, IEEE Transactions on Automatic Control, 56 (2011), 923. doi: 10.1109/TAC.2010.2103416.
[18]	J. Kim, K. Kim, V. Natarajan, S. Kelly and J. Bentsman, PdE-based model reference adaptive control of uncertain heterogeneous multiagent networks,, Nonlinear Analysis: Hybrid Systems, 2 (2008), 1152. doi: 10.1016/j.nahs.2008.09.008.
[19]	J. Kim, V. Natarajan, S. Kelly and J. Bentsman, Disturbance rejection in robust PdE-based MRAC laws for uncertain heterogeneous multiagent networks under boundary reference,, Nonlinear Analysis: Hybrid Systems, 4 (2010), 484. doi: 10.1016/j.nahs.2009.11.005.
[20]	M. Krstic and A. Smyshlyaev, Boundary Control of PDEs: A Course on Backstepping Designs,, SIAM, (2008). doi: 10.1137/1.9780898718607.
[21]	Z. Lin, Distributed Control and Analysis of Coupled Cell Systems,, VDM Verlag, (2008).
[22]	W. Litvinov, Optimal control of electrorheological clutch described by nonlinear parabolic equation with nonlocal boundary conditions,, Journal of Industrial and Management Optimization, 7 (2011), 291. doi: 10.3934/jimo.2011.7.291.
[23]	M. Liu, S. Zang and D. Zhou, Fast leak detection and location of gas pipelines based on an adaptive particle filter,, International Journal of Applied Mathematics and Computer Science, 15 ().
[24]	M. Mesbahi and M. Egerstedt, Graph Theoretic Methods in Multiagent Networks (In Applied Mathematics Series),, Princeton University Press, (2010).
[25]	T. Meurer and M. Krstic, Finite-time multi-agent deployment: A nonlinear pde motion planning approach,, Automatica, 47 (2011), 2534. doi: 10.1016/j.automatica.2011.08.045.
[26]	S. Moura and H. Fathy, Optimal boundary control & estimation of diffusion-reaction PDEs,, in Proceeding of the Conference on Decision and Control, (2011), 921.
[27]	R. Murray, Recent research in cooperative control of multi-vehicle systems,, Journal of Dynamical Systems, (): 571.
[28]	R. Olfati-Saber and R. Murray, Consensus problems in networks of agents with switching topology and time-delays,, IEEE Transactions on Automatic Control, 49 (2004), 1520. doi: 10.1109/TAC.2004.834113.
[29]	P. Parfomak, Pipeline Safety and Security: Federal Programs,, Congress Research Services (CRS) Report for Congress, (2008).
[30]	M. Rafiee, Q. Wu and A. Bayen, Kalman filter based estimation of flow states in open channels using Lagrangian sensing,, Proceedings of the Conference on Decision and Control, (2009), 8266. doi: 10.1109/CDC.2009.5400661.
[31]	W. Ren and Y. Cao, Distributed Coordination of Multi-agent Networks,, (Communications and Control Engineering Series) Springer-Verlag, (2011).
[32]	A. Sarlette and R. Sepulchre, A PDE viewpoint on basic properties of coordination algorithms with symmetries,, in Proceedings of the Conference on Decision and Control, (2009), 5139. doi: 10.1109/CDC.2009.5400570.
[33]	J. Strikwerda, Finite Difference Schemes and Partial Differential Equations, 2nd Edition,, SIAM, (2004). doi: 10.1137/1.9780898717938.
[34]	F. Tröltzsch, Optimal Control of Partial Differential Equations: Theory, Methods and Applications (Graduate Studies in Mathematics),, American Mathematical Society, (2010).
[35]	G. Wang and H. Ye, Leakage Detection and Localization of Long Distance Fluid Pipelines,, Tsinghua University Press, (2010).
[36]	Z. Wang, H. Zhang, J. Feng and S. Lun, Present situation and prospect on leak detection and localization techniques for long distance fluid transport pipeline,, Control and Instruments in Chemical Industry, 30 (2003), 5.
[37]	S. Woon, V. Rehbock and R. Loxton, Global optimization method for continuous-time sensor scheduling,, Nonlinear Dynamics and Systems Theory, 10 (2010), 175.
[38]	S. Woon, V. Rehbock and R. Loxton, Towards global solutions of optimal discrete-valued control problems,, Optimal Control Applications and Methods, 33 (2012), 576. doi: 10.1002/oca.1015.
[39]	K. Yiu, K. Mak and K. Teo, Airfoil design via optimal control theory,, Journal of Industrial and Management Optimization, 1 (2005), 133. doi: 10.3934/jimo.2005.1.133.
[40]	C. Yu, B. Li, R. Loxton and K. Teo, Optimal discrete-valued control computation,, Journal of Global Optimization, 56 (2013), 503. doi: 10.1007/s10898-012-9858-7.

show all references

References:

[1]	N. Ahmed and K. Teo, Optimal Control of Distributed Parameter Systems,, North Holland, (1981).
[2]	S. Anita, V. Arnautu and V. Capasso, An Introduction to Optimal Control Problems in Life Sciences and Economics,, Modeling and Simulation in Science, (2011). doi: 10.1007/978-0-8176-8098-5.
[3]	V. Arnautu and P. Neittaanmaki, Optimal Control from Theory to Computer Programs,, Kluwer Academic, (2003). doi: 10.1007/978-94-017-2488-3.
[4]	P. Barooah, P. Mehta and J. Hespanha, Mistuning-based control design to improve closed-loop stability margin of vehicular platoons,, IEEE Transactions on Automatic Control, 54 (2009), 2100. doi: 10.1109/TAC.2009.2026934.
[5]	S. Blazic, D. Matko and G. Geiger, Simple model of a multi-batch driven pipeline,, Mathematics and Computers in Simulation, 64 (2004), 617. doi: 10.1016/j.matcom.2003.11.013.
[6]	F. Bullo, J. Cortes and S. Martinez, Distributed Control of Robotic Networks (In Applied Mathematics Series),, Princeton University Press, (2009).
[7]	M. Chen and D. Georges, Nonlinear optimal control of an open-channel hydraulic system based on an infinite-dimensional model,, in Proceeding of the Conference on Decision and Control, (1999).
[8]	H. Cho and G. Hwang, Optimal design for dynamic spectrum access in cognitive radio networks under rayleigh fading,, Journal of Industrial and Management Optimization, 8 (2012), 821. doi: 10.3934/jimo.2012.8.821.
[9]	E. Chow, L. Hendrix, M. Herberg, S. Itoh, B. Kong, M. Lall and P. Srevens, Pipeline Politics in Asia: The Intersection of Demand, Energy Markets, and Supply Routes,, National Bureau of Asian Research, (2010).
[10]	Y. Ding and S. Wang, Optimal control of open-channel flow using adjoint sensitivity analysis,, Journal of Hydraulic Engineering-ASCE, 132 (2006), 1215. doi: 10.1061/(ASCE)0733-9429(2006)132:11(1215).
[11]	Z. Feng, K. Teo and V. Rehbock, Branch and bound method for sensor scheduling in discrete time,, Journal of Industrial and Management Optimization, 1 (2005), 499. doi: 10.3934/jimo.2005.1.499.
[12]	Z. Feng, K. Teo and V. Rehbock, Hybrid method for a general optimal sensor scheduling problem in discrete time,, Automatica, 44 (2008), 1295. doi: 10.1016/j.automatica.2007.09.024.
[13]	G. Ferrari-Trecate, A. Buffa and M. Gati, Analysis of coordination in multi-agent systems through partial difference equations,, IEEE Transactions on Automatic Control, 51 (2006), 1058. doi: 10.1109/TAC.2006.876805.
[14]	P. Frihauf and M. Krstic, Leader-enabled deployment onto planar curves: A pde-based approach,, IEEE Transactions on Automatic Control, 56 (2011), 1791. doi: 10.1109/TAC.2010.2092210.
[15]	R. Glowinski, J. Lions and J. He, Exact and Approximate Controllability for Distributed Parameter Systems: A Numerical Approach,, (Encyclopedia of Mathematics and its Applications) Cambridge University Press, (2008). doi: 10.1017/CBO9780511721595.
[16]	H. Hao and P. Barooah, On achieving size-independent stability margin of vehicular lattice formations with distributed control,, IEEE Transactions on Automatic Control, 57 (2012), 2688. doi: 10.1109/TAC.2012.2191179.
[17]	H. Hao, P. Barooah and P. Mehta, Stability margin scaling laws for distributed formation control as a function of network structure,, IEEE Transactions on Automatic Control, 56 (2011), 923. doi: 10.1109/TAC.2010.2103416.
[18]	J. Kim, K. Kim, V. Natarajan, S. Kelly and J. Bentsman, PdE-based model reference adaptive control of uncertain heterogeneous multiagent networks,, Nonlinear Analysis: Hybrid Systems, 2 (2008), 1152. doi: 10.1016/j.nahs.2008.09.008.
[19]	J. Kim, V. Natarajan, S. Kelly and J. Bentsman, Disturbance rejection in robust PdE-based MRAC laws for uncertain heterogeneous multiagent networks under boundary reference,, Nonlinear Analysis: Hybrid Systems, 4 (2010), 484. doi: 10.1016/j.nahs.2009.11.005.
[20]	M. Krstic and A. Smyshlyaev, Boundary Control of PDEs: A Course on Backstepping Designs,, SIAM, (2008). doi: 10.1137/1.9780898718607.
[21]	Z. Lin, Distributed Control and Analysis of Coupled Cell Systems,, VDM Verlag, (2008).
[22]	W. Litvinov, Optimal control of electrorheological clutch described by nonlinear parabolic equation with nonlocal boundary conditions,, Journal of Industrial and Management Optimization, 7 (2011), 291. doi: 10.3934/jimo.2011.7.291.
[23]	M. Liu, S. Zang and D. Zhou, Fast leak detection and location of gas pipelines based on an adaptive particle filter,, International Journal of Applied Mathematics and Computer Science, 15 ().
[24]	M. Mesbahi and M. Egerstedt, Graph Theoretic Methods in Multiagent Networks (In Applied Mathematics Series),, Princeton University Press, (2010).
[25]	T. Meurer and M. Krstic, Finite-time multi-agent deployment: A nonlinear pde motion planning approach,, Automatica, 47 (2011), 2534. doi: 10.1016/j.automatica.2011.08.045.
[26]	S. Moura and H. Fathy, Optimal boundary control & estimation of diffusion-reaction PDEs,, in Proceeding of the Conference on Decision and Control, (2011), 921.
[27]	R. Murray, Recent research in cooperative control of multi-vehicle systems,, Journal of Dynamical Systems, (): 571.
[28]	R. Olfati-Saber and R. Murray, Consensus problems in networks of agents with switching topology and time-delays,, IEEE Transactions on Automatic Control, 49 (2004), 1520. doi: 10.1109/TAC.2004.834113.
[29]	P. Parfomak, Pipeline Safety and Security: Federal Programs,, Congress Research Services (CRS) Report for Congress, (2008).
[30]	M. Rafiee, Q. Wu and A. Bayen, Kalman filter based estimation of flow states in open channels using Lagrangian sensing,, Proceedings of the Conference on Decision and Control, (2009), 8266. doi: 10.1109/CDC.2009.5400661.
[31]	W. Ren and Y. Cao, Distributed Coordination of Multi-agent Networks,, (Communications and Control Engineering Series) Springer-Verlag, (2011).
[32]	A. Sarlette and R. Sepulchre, A PDE viewpoint on basic properties of coordination algorithms with symmetries,, in Proceedings of the Conference on Decision and Control, (2009), 5139. doi: 10.1109/CDC.2009.5400570.
[33]	J. Strikwerda, Finite Difference Schemes and Partial Differential Equations, 2nd Edition,, SIAM, (2004). doi: 10.1137/1.9780898717938.
[34]	F. Tröltzsch, Optimal Control of Partial Differential Equations: Theory, Methods and Applications (Graduate Studies in Mathematics),, American Mathematical Society, (2010).
[35]	G. Wang and H. Ye, Leakage Detection and Localization of Long Distance Fluid Pipelines,, Tsinghua University Press, (2010).
[36]	Z. Wang, H. Zhang, J. Feng and S. Lun, Present situation and prospect on leak detection and localization techniques for long distance fluid transport pipeline,, Control and Instruments in Chemical Industry, 30 (2003), 5.
[37]	S. Woon, V. Rehbock and R. Loxton, Global optimization method for continuous-time sensor scheduling,, Nonlinear Dynamics and Systems Theory, 10 (2010), 175.
[38]	S. Woon, V. Rehbock and R. Loxton, Towards global solutions of optimal discrete-valued control problems,, Optimal Control Applications and Methods, 33 (2012), 576. doi: 10.1002/oca.1015.
[39]	K. Yiu, K. Mak and K. Teo, Airfoil design via optimal control theory,, Journal of Industrial and Management Optimization, 1 (2005), 133. doi: 10.3934/jimo.2005.1.133.
[40]	C. Yu, B. Li, R. Loxton and K. Teo, Optimal discrete-valued control computation,, Journal of Global Optimization, 56 (2013), 503. doi: 10.1007/s10898-012-9858-7.

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